794 search results - page 47 / 159 » Optimization Techniques for Semi-Supervised Support Vector M... |
ALT
2004
Springer
14 years 6 months ago
2004
Springer
The decomposition method is currently one of the major methods for solving the convex quadratic optimization problems being associated with support vector machines. For a special c...
ICML
2006
IEEE
14 years 10 months ago
2006
IEEE
We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of Conditional Random Fields (CRFs). On several larg...
GECCO
2010
Springer
14 years 15 days ago
2010
Springer
Most surrogate approaches to multi-objective optimization build a surrogate model for each objective. These surrogates can be used inside a classical Evolutionary Multiobjective O...
FLAIRS
2008
13 years 11 months ago
2008
In this paper, we model large support vector machines (SVMs) by smaller networks in order to decrease the computational cost. The key idea is to generate additional training patte...
ICANN
2007
Springer
14 years 3 months ago
2007
Springer
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...